iBRDF

The BRDF models represented in the previous sections can capture
subtle differences in surface light reflection. In order to generate
synthetic images using BRDFs containing this level of generality requires
a shader capable of capturing the detail which is available in the
BRDFs. A new shader an extension of Radiance, called iBRDF, has been
developed which accurately imitates this detail through its ability
to utilize arbitrary BRDF functions.

We have developed an efficient method of performing this Monte Carlo
integration. Instead of casting rays in a uniform distribution about
the hemisphere and weighting the returned value by the reflectance,
the ray distribution itself is weighted by the reflectance. This can
be done in a straightforward manner when the BRDF is composed of invertible
functions such as Gaussians. When the BRDF is represented discretely,
either by taking measurements over the hemisphere or by sampling a
non-invertible functional form, another method must be used to generate
random variates for Monte Carlo integration. This can be accomplished
by first subtracting the smallest hemisphere that fits within the
BRDF data. This removes the diffuse or uniformly varying portion of
the BRDF and leaves only the highly directional specular part. Walker's
alias selection method [WALKE77]
can be employed to create random variates from these remaining specular
reflectances

The images in Figure 8 below display the improvement iBRDF offers
in rendering surfaces modelled with arbitrary BRDFs. The top image
which uses the built-in BRDF shader of Radiance, reflects the lights
correctly, but there is no reflection at all of the indirect illumination
from the surrounding checkered floor. Performing uniform sampling
of the BRDF begins to captures this indirect contribution as seen
in the middle figure, but the reflected image of the floor contains
excessive noise. The best results are obtained with the importance
sampling of iBRDF in the bottom figure. The reflection of the floor
is accurately captured in the four spheres of this image using the
same number of samples as the middle image.